# Any member of the JuliaNLSolvers organization here?

**URL:** <https://discourse.julialang.org/t/any-member-of-the-julianlsolvers-organization-here/135722>\
**Category:** General Usage\
**Tags:** question, package, nlsolve\
**Created:** [February 18, 2026, 11:10am UTC](https://discourse.julialang.org/t/any-member-of-the-julianlsolvers-organization-here/135722 "2026-02-18T11:10:05Z")\
**Posts on this page:** 11\
**Page:** 1

<div class="post-metadata">

**Author:** ![ufechner7](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/ufechner7/32/51363_2.png) [@ufechner7](https://discourse.julialang.org/u/ufechner7)\
**Post date:** [February 18, 2026, 11:10am UTC](https://discourse.julialang.org/t/any-member-of-the-julianlsolvers-organization-here/135722/1 "2026-02-18T11:10:05Z")

</div>

Is there anyone from the JuliaNLSolvers organization here? I see the organization has only two members: [JuliaNLSolvers · GitHub](https://github.com/JuliaNLSolvers)

Perhaps a good time to look for additional members?

Someone should approve this workflow: [handle underflow of norm(J[:,i])^2 by stevengj · Pull Request #296 · JuliaNLSolvers/NLsolve.jl · GitHub](https://github.com/JuliaNLSolvers/NLsolve.jl/pull/296)

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<div class="post-metadata">

**Author:** ![ChrisRackauckas](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/chrisrackauckas/32/77_2.png) [@ChrisRackauckas](https://discourse.julialang.org/u/ChrisRackauckas)\
**Post date:** [February 19, 2026, 4:25am UTC](https://discourse.julialang.org/t/any-member-of-the-julianlsolvers-organization-here/135722/2 "2026-02-19T04:25:13Z")

</div>

For reference, NonlinearSolve.jl handles this effectively:

> <https://github.com/SciML/NonlinearSolve.jl/issues/835>
>
> \## Reference
> 
> NLsolve.jl PR: https://github.com/JuliaNLSolvers/NLsolve.jl/pull/2…96
> Discourse thread: https://discourse.julialang.org/t/bug-in-nlsolve/135660
> 
> \## The NLsolve.jl bug
> 
> NLsolve.jl's trust region dogleg implementation computes Jacobian column norms for autoscaling:
> 
> \`\`\`julia
> cache.d\[j\] = norm(view(jacobian(df), :, j))
> if cache.d\[j\] == zero(cache.d\[j\])
> cache.d\[j\] = one(cache.d\[j\])
> end
> \`\`\`
> 
> Later it divides by \`d.^2\`. When column norms are tiny but nonzero (e.g. \`~1e-200\`), the norm passes the \`== 0\` check, but \`d\[j\]^2\` underflows to \`0.0\`, causing division-by-zero and NaN propagation.
> 
> \## NonlinearSolve.jl is not affected
> 
> Tested with the reproducing example from the Discourse thread (Jacobian with \`1e-200\` column entries) — NonlinearSolve.jl produces no NaN, no Inf, no crash. The solvers return \`Stalled\` or \`MaxIters\` gracefully (the test system is intentionally inconsistent).
> 
> \### Why it's robust
> 
> \*\*TrustRegion (Dogleg):\*\* The dogleg implementation (\`NonlinearSolveBase/src/descent/dogleg.jl\`) does not use Jacobian-column-norm autoscaling at all. It computes norms of step directions (\`l\_grad = internalnorm(δu\_cauchy)\`) rather than Jacobian columns, so the \`norm(J\[:,j\])^2 → underflow\` pattern never occurs.
> 
> \*\*LevenbergMarquardt:\*\* The LM implementation (\`NonlinearSolveFirstOrder/src/levenberg\_marquardt.jl\`) computes \`sum(abs2, J; dims=1)\` (squared column norms) for the diagonal damping matrix \`DᵀD\`. However, \`DᵀD\` is initialized with a \`min\_damping\_D\` floor (default \`1e-8\`) and \`update\_levenberg\_marquardt\_diagonal!!\` uses \`max(y.diag\[i\], x\[i\])\`, so diagonal entries can never go below \`1e-8\`. This prevents the underflow-to-zero problem.
> 
> \## Test code
> 
> \`\`\`julia
> using NonlinearSolve
> 
> function f!(F, x, p)
> F\[1\] = x\[1\] - 1.0
> F\[2\] = x\[1\]^2 - 4.0
> end
> 
> function j!(J, x, p)
> J\[1, 1\] = 1.0
> J\[2, 1\] = 2.0 \* x\[1\]
> J\[1, 2\] = 1e-200
> J\[2, 2\] = 1e-200
> end
> 
> x0 = \[0.5, 0.5\]
> prob = NonlinearProblem(NonlinearFunction(f!; jac=j!), x0, nothing)
> 
> sol\_tr = solve(prob, TrustRegion()) # Stalled, no NaN
> sol\_lm = solve(prob, LevenbergMarquardt()) # MaxIters, no NaN
> \`\`\`
> 
> This issue is for documentation/reference purposes only — no code changes needed.

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<div class="post-metadata">

**Author:** ![ufechner7](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/ufechner7/32/51363_2.png) [@ufechner7](https://discourse.julialang.org/u/ufechner7)\
**Post date:** [February 19, 2026, 5:32am UTC](https://discourse.julialang.org/t/any-member-of-the-julianlsolvers-organization-here/135722/3 "2026-02-19T05:32:25Z")

</div>

Just to be clear: AI and I spent three hours migrating to NonlinearSolve. It doesn’t work. It cannot solve the problem that NLsolve handles easily. Therefore, for me, maintaining and fixing NLsolve is essential.

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<div class="post-metadata">

**Author:** ![ChrisRackauckas](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/chrisrackauckas/32/77_2.png) [@ChrisRackauckas](https://discourse.julialang.org/u/ChrisRackauckas)\
**Post date:** [February 19, 2026, 5:37am UTC](https://discourse.julialang.org/t/any-member-of-the-julianlsolvers-organization-here/135722/4 "2026-02-19T05:37:59Z")

</div>

What’s your MWE?

---

<div class="post-metadata">

**Author:** ![ufechner7](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/ufechner7/32/51363_2.png) [@ufechner7](https://discourse.julialang.org/u/ufechner7)\
**Post date:** [February 19, 2026, 5:46am UTC](https://discourse.julialang.org/t/any-member-of-the-julianlsolvers-organization-here/135722/5 "2026-02-19T05:46:14Z")

</div>

This code works: [KiteModels.jl/test/test-steady-state-kps4.jl at bestie · OpenSourceAWE/KiteModels.jl · GitHub](https://github.com/OpenSourceAWE/KiteModels.jl/blob/bestie/test/test-steady-state-kps4.jl)

The same code with NonlinearSolve doesn’t work. I do not yet have an MWE as proof.

---

<div class="post-metadata">

**Author:** ![ChrisRackauckas](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/chrisrackauckas/32/77_2.png) [@ChrisRackauckas](https://discourse.julialang.org/u/ChrisRackauckas)\
**Post date:** [February 19, 2026, 5:53am UTC](https://discourse.julialang.org/t/any-member-of-the-julianlsolvers-organization-here/135722/6 "2026-02-19T05:53:47Z")

</div>

I’ll take it from there.

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<div class="post-metadata">

**Author:** ![ChrisRackauckas](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/chrisrackauckas/32/77_2.png) [@ChrisRackauckas](https://discourse.julialang.org/u/ChrisRackauckas)\
**Post date:** [February 19, 2026, 10:01am UTC](https://discourse.julialang.org/t/any-member-of-the-julianlsolvers-organization-here/135722/7 "2026-02-19T10:01:04Z")

</div>

I ran that code with NonlinearSolve TrustRegion and… it just worked out of the box, it even passed the one test that NLsolve.jl didn’t pass.

> <https://github.com/SciML/NonlinearSolve.jl/issues/836>
>
> \## Context
> 
> \[KiteModels.jl\](https://github.com/OpenSourceAWE/KiteModels.jl) uses… \`NLsolve.jl\` to find the steady-state equilibrium of a 4-point kite power system (3D mass-spring network with aerodynamic forces). We'd like to migrate to \`NonlinearSolve.jl\` but the current code relies on several NLsolve-specific features.
> 
> \## Current NLsolve usage
> 
> The core call pattern is:
> 
> \`\`\`julia
> using NLsolve
> 
> \# Manual central finite-difference Jacobian with subnormal flushing
> function make\_jac(f!, n\_vars)
> \_F1 = zeros(Float64, n\_vars)
> \_F2 = zeros(Float64, n\_vars)
> \_xp = zeros(Float64, n\_vars)
> \_xm = zeros(Float64, n\_vars)
> threshold = sqrt(floatmin(Float64))
> function jac!(J, x)
> h\_factor = cbrt(eps(Float64))
> for j in 1:n\_vars
> copyto!(\_xp, x); copyto!(\_xm, x)
> h = max(abs(x\[j\]), one(Float64)) \* h\_factor
> \_xp\[j\] += h; \_xm\[j\] -= h
> f!(\_F1, \_xp); f!(\_F2, \_xm)
> @views J\[:, j\] .= (\_F1 .- \_F2) ./ (2h)
> end
> @. J = ifelse(abs(J) \< threshold, zero(Float64), J)
> end
> return jac!
> end
> 
> n\_unknowns = 20 # 2\*(segments + kite\_particles - 1) + 2
> X00 = zeros(Float64, n\_unknowns)
> jac! = make\_jac(f!, n\_unknowns)
> results = nlsolve(f!, jac!, X00;
> autoscale=true, xtol=4e-7, ftol=4e-7, iterations=200)
> if NLsolve.converged(results)
> solution = results.zero
> end
> \`\`\`
> 
> \### NLsolve features we depend on
> 
> 1. \*\*Manual Jacobian (\`jac!\`)\*\*: Needed because \`NLSolversBase \>= 7.10\` produces subnormal Jacobian entries via DifferentiationInterface, which cause NaN in NLsolve's autoscale (subnormal column norms squared underflow to zero). The manual Jacobian flushes near-zero entries.
> 
> 2. \*\*\`autoscale=true\`\*\*: Critical for convergence — the system variables have very different scales (positions in meters vs. small perturbations).
> 
> 3. \*\*Separate \`xtol\` and \`ftol\`\*\*: Both set to \`4e-7\`.
> 
> 4. \*\*\`iterations\` limit\*\*: Set to 200.
> 
> 5. \*\*\`results.zero\`\*\* and \*\*\`converged(results)\`\*\*: Solution extraction and convergence check.
> 
> \### Questions
> 
> 1. What is the equivalent \`NonlinearSolve.jl\` API for this call pattern?
> 2. Does NonlinearSolve handle autoscaling? (I see \[#425\](https://github.com/SciML/NonlinearSolve.jl/issues/425) is open for trust region autoscaling.)
> 3. Does NonlinearSolve's automatic differentiation avoid the subnormal Jacobian issue, or would we still need a manual Jacobian?
> 4. What's the recommended solver algorithm for this kind of problem (20-variable nonlinear system from physics, starting from a reasonable initial guess)?
> 
> \## Self-contained MWE
> 
> Below is a \*\*complete, self-contained\*\* MWE (~960 lines) that reproduces the KiteModels.jl steady-state test without any kite-specific package dependencies. It models a 4-point kite on a segmented tether with aerodynamic forces, spring/damping, and a winch. The nonlinear solve finds particle positions where all accelerations vanish (steady-state equilibrium).
> 
> \*\*Dependencies\*\*: \`StaticArrays\`, \`LinearAlgebra\`, \`NLsolve\`, \`Dierckx\`, \`Test\`
> 
> \<details\>
> \<summary\>Click to expand full MWE (mwe\_steady\_state\_kps4.jl)\</summary\>
> 
> \`\`\`julia
> $(cat /home/crackauc/sandbox/tmp\_20260219\_005256\_56738/mwe\_steady\_state\_kps4.jl)
> \`\`\`
> 
> \</details\>
> 
> \### Running the MWE
> 
> \`\`\`julia
> \] add StaticArrays NLsolve Dierckx
> include("mwe\_steady\_state\_kps4.jl")
> \`\`\`
> 
> Expected output (all 15 tests pass):
> \`\`\`
> l=100.0: tether\_length=100.92196416459542, pre\_tension=1.0003226874576083 ✓
> l=200.0: tether\_length=202.59541320501268, pre\_tension=1.0004541973108771 ✓
> l=392.0: tether\_length=399.15270436705833, pre\_tension=1.0006386343184874 ✓
> Test Summary: | Pass Total Time
> test\_find\_steady\_state (MWE) | 15 15 15.3s
> \`\`\`
> 
> \## Environment
> 
> \- Julia 1.11
> \- NLsolve v4.5.1
> \- StaticArrays v1.9.16

So here’s a PR which passes all of your tests locally:

> <https://github.com/OpenSourceAWE/KiteModels.jl/pull/261>
>
> \## Summary
> 
> \- Replaces \`NLsolve.jl\` trust region dogleg with \`NonlinearSolve.jl\`… \`TrustRegion()\` in both \`KPS3\` and \`KPS4\` \`find\_steady\_state!\` functions
> \- Removes \`NLsolve\` and \`NLSolversBase\` as direct dependencies (NonlinearSolve was already a transitive dependency via OrdinaryDiffEqNonlinearSolve)
> \- Retains the custom finite-difference Jacobian (\`make\_jac\`) since the model's \`MVector{3, Float64}\` internals cannot hold \`ForwardDiff.Dual\` numbers
> 
> \## Motivation
> 
> NLsolve.jl has known issues with subnormal Jacobian entries from NLSolversBase \>= 7.10 (see PR #259). Rather than pinning NLSolversBase or maintaining workarounds, this PR switches to NonlinearSolve.jl which:
> 
> 1. \*\*Already works\*\* — \`TrustRegion()\` passes all 452 tests (441 pass + 11 pre-existing broken)
> 2. \*\*Produces better results\*\* — On the l=392 steady-state test case, NonlinearSolve TrustRegion achieves 0.92% tether length error vs NLsolve's 1.35% (which fails the 1% rtol check)
> 3. \*\*Is faster\*\* — ~0.03s vs ~0.15s per solve (post-JIT)
> 4. \*\*Is already a dependency\*\* — No new packages added to the dependency tree
> 5. \*\*Doesn't need autoscale\*\* — NLsolve's \`autoscale=true\` (Moré/MINPACK diagonal scaling) is unnecessary with NonlinearSolve's TrustRegion
> 
> \## Changes
> 
> | File | Change |
> |------|--------|
> | \`src/KPS4.jl\` | Replace \`nlsolve()\` call with \`NonlinearProblem\` + \`solve(prob, TrustRegion())\` |
> | \`src/KPS3.jl\` | Same replacement |
> | \`src/KiteModels.jl\` | Remove \`NLsolve\` from \`using\`, add \`import SciMLBase\` |
> | \`src/init.jl\` | Update \`make\_jac\` docstring |
> | \`Project.toml\` | Remove NLsolve/NLSolversBase deps, add SciMLBase |
> | \`test/Project.toml\` | Remove NLsolve dep |
> | \`examples\_3d/Project.toml\` | Remove NLsolve dep |
> | \`test/create\_sys\_image.jl\` | Remove NLsolve from sysimage |
> 
> \## Test plan
> 
> \- \[x\] All 15 KPS4 steady-state tests pass
> \- \[x\] All 67 KPS3 tests pass
> \- \[x\] Full \`Pkg.test()\` passes: 441 pass + 11 pre-existing broken, 0 failures
> 
> \## Related
> 
> \- NonlinearSolve.jl issue: https://github.com/SciML/NonlinearSolve.jl/issues/836
> \- KiteModels.jl PR #259 (NLSolversBase subnormal workaround)
> 
> 🤖 Generated with \[Claude Code\](https://claude.com/claude-code)

Is there some test there that isn’t in the repo?

---

<div class="post-metadata">

**Author:** ![ufechner7](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/ufechner7/32/51363_2.png) [@ufechner7](https://discourse.julialang.org/u/ufechner7)\
**Post date:** [February 19, 2026, 10:16am UTC](https://discourse.julialang.org/t/any-member-of-the-julianlsolvers-organization-here/135722/8 "2026-02-19T10:16:43Z")

</div>

It doesn’t pass the tests locally:

```julia-auto
julia> include("test/test-steady-state-kps4.jl")
  Activating project at `~/repos/KiteModels.jl/test`
┌ Warning: find_steady_state!: solver did not converge! retcode=Stalled
└ @ KiteModels ~/repos/KiteModels.jl/src/KPS4.jl:704
test_find_steady_state: Test Failed at /home/ufechner/repos/KiteModels.jl/test/test-steady-state-kps4.jl:42
  Expression: pre_tension > 1.0001
   Evaluated: 1.0 > 1.0001

Stacktrace:
 [1] macro expansion
   @ ~/.julia/juliaup/julia-1.11.9+0.x64.linux.gnu/share/julia/stdlib/v1.11/Test/src/Test.jl:680 [inlined]
 [2] macro expansion
   @ ~/repos/KiteModels.jl/test/test-steady-state-kps4.jl:42 [inlined]
 [3] macro expansion
   @ ~/.julia/juliaup/julia-1.11.9+0.x64.linux.gnu/share/julia/stdlib/v1.11/Test/src/Test.jl:1709 [inlined]
 [4] top-level scope
   @ ~/repos/KiteModels.jl/test/test-steady-state-kps4.jl:30
┌ Warning: find_steady_state!: solver did not converge! retcode=MaxIters
└ @ KiteModels ~/repos/KiteModels.jl/src/KPS4.jl:704
test_find_steady_state: Test Failed at /home/ufechner/repos/KiteModels.jl/test/test-steady-state-kps4.jl:42
  Expression: pre_tension > 1.0001
   Evaluated: 1.0 > 1.0001

Stacktrace:
 [1] macro expansion
   @ ~/.julia/juliaup/julia-1.11.9+0.x64.linux.gnu/share/julia/stdlib/v1.11/Test/src/Test.jl:680 [inlined]
 [2] macro expansion
   @ ~/repos/KiteModels.jl/test/test-steady-state-kps4.jl:42 [inlined]
 [3] macro expansion
   @ ~/.julia/juliaup/julia-1.11.9+0.x64.linux.gnu/share/julia/stdlib/v1.11/Test/src/Test.jl:1709 [inlined]
 [4] top-level scope
   @ ~/repos/KiteModels.jl/test/test-steady-state-kps4.jl:30
test_find_steady_state: Test Failed at /home/ufechner/repos/KiteModels.jl/test/test-steady-state-kps4.jl:45
  Expression: isapprox(tether_length(kps4_local), 1.008954l, rtol = 0.01)
   Evaluated: isapprox(197.42057783848486, 201.7908; rtol = 0.01)

Stacktrace:
 [1] macro expansion
   @ ~/.julia/juliaup/julia-1.11.9+0.x64.linux.gnu/share/julia/stdlib/v1.11/Test/src/Test.jl:680 [inlined]
 [2] macro expansion
   @ ~/repos/KiteModels.jl/test/test-steady-state-kps4.jl:45 [inlined]
 [3] macro expansion
   @ ~/.julia/juliaup/julia-1.11.9+0.x64.linux.gnu/share/julia/stdlib/v1.11/Test/src/Test.jl:1709 [inlined]
 [4] top-level scope
   @ ~/repos/KiteModels.jl/test/test-steady-state-kps4.jl:30
┌ Warning: find_steady_state!: solver did not converge! retcode=MaxIters
└ @ KiteModels ~/repos/KiteModels.jl/src/KPS4.jl:704
test_find_steady_state: Test Failed at /home/ufechner/repos/KiteModels.jl/test/test-steady-state-kps4.jl:42
  Expression: pre_tension > 1.0001
   Evaluated: 1.0 > 1.0001

Stacktrace:
 [1] macro expansion
   @ ~/.julia/juliaup/julia-1.11.9+0.x64.linux.gnu/share/julia/stdlib/v1.11/Test/src/Test.jl:680 [inlined]
 [2] macro expansion
   @ ~/repos/KiteModels.jl/test/test-steady-state-kps4.jl:42 [inlined]
 [3] macro expansion
   @ ~/.julia/juliaup/julia-1.11.9+0.x64.linux.gnu/share/julia/stdlib/v1.11/Test/src/Test.jl:1709 [inlined]
 [4] top-level scope
   @ ~/repos/KiteModels.jl/test/test-steady-state-kps4.jl:30
test_find_steady_state: Test Failed at /home/ufechner/repos/KiteModels.jl/test/test-steady-state-kps4.jl:45
  Expression: isapprox(tether_length(kps4_local), 1.008954l, rtol = 0.01)
   Evaluated: isapprox(389.9800737647081, 395.50996799999996; rtol = 0.01)

Stacktrace:
 [1] macro expansion
   @ ~/.julia/juliaup/julia-1.11.9+0.x64.linux.gnu/share/julia/stdlib/v1.11/Test/src/Test.jl:680 [inlined]
 [2] macro expansion
   @ ~/repos/KiteModels.jl/test/test-steady-state-kps4.jl:45 [inlined]
 [3] macro expansion
   @ ~/.julia/juliaup/julia-1.11.9+0.x64.linux.gnu/share/julia/stdlib/v1.11/Test/src/Test.jl:1709 [inlined]
 [4] top-level scope
   @ ~/repos/KiteModels.jl/test/test-steady-state-kps4.jl:30
Test Summary: | Pass Fail Total Time
test_find_steady_state | 10 5 15 1.6s
ERROR: LoadError: Some tests did not pass: 10 passed, 5 failed, 0 errored, 0 broken.
in expression starting at /home/ufechner/repos/KiteModels.jl/test/test-steady-state-kps4.jl:29

```

For whatever reason, the only test that was running on your pull request on Github was the test if the licenses are correct: [Replace NLsolve.jl with NonlinearSolve.jl TrustRegion · OpenSourceAWE/KiteModels.jl@eb90218 · GitHub](https://github.com/OpenSourceAWE/KiteModels.jl/actions/runs/22177034989/job/64129927626?pr=261)

---

<div class="post-metadata">

**Author:** ![ChrisRackauckas](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/chrisrackauckas/32/77_2.png) [@ChrisRackauckas](https://discourse.julialang.org/u/ChrisRackauckas)\
**Post date:** [February 19, 2026, 11:30am UTC](https://discourse.julialang.org/t/any-member-of-the-julianlsolvers-organization-here/135722/9 "2026-02-19T11:30:38Z")

</div>

It’s a difference of Julia v1.12 vs v1.11. Interesting.

---

<div class="post-metadata">

**Author:** ![ChrisRackauckas](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/chrisrackauckas/32/77_2.png) [@ChrisRackauckas](https://discourse.julialang.org/u/ChrisRackauckas)\
**Post date:** [February 20, 2026, 5:22am UTC](https://discourse.julialang.org/t/any-member-of-the-julianlsolvers-organization-here/135722/10 "2026-02-20T05:22:58Z")

</div>

Found it and fixed. That was an interesting computer and Julia-version specific bug 😅 but it should all be good now.

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<div class="post-metadata">

**Author:** ![pleiby](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/pleiby/32/8355_2.png) [@pleiby](https://discourse.julialang.org/u/pleiby)\
**Post date:** [February 24, 2026, 7:30pm UTC](https://discourse.julialang.org/t/any-member-of-the-julianlsolvers-organization-here/135722/11 "2026-02-24T19:30:11Z")

</div>

If I may, you continue to amaze me Chris. Thanks!